2D array indexing (row, col) in NumPy - Mini Project: Build & Apply

2D Array Indexing with NumPy

📖 Scenario: You are working with a small grid of temperature readings from different sensors arranged in rows and columns. You want to access specific readings by their row and column positions.

🎯 Goal: Learn how to create a 2D NumPy array and access its elements using row and column indexes.

📋 What You'll Learn

Create a 2D NumPy array with exact values

Define variables for row and column indexes

Use these indexes to access the correct element in the array

Print the accessed element

💡 Why This Matters

🌍 Real World

Accessing specific data points in grids or tables is common in weather data, images, and spreadsheets.

💼 Career

Data scientists often need to extract and analyze specific values from multi-dimensional data arrays.

1

Create a 2D NumPy array

Import NumPy as np and create a 2D NumPy array called temps with these exact values: [[23, 25, 22], [21, 24, 20], [19, 22, 23]].

NumPy

import numpy as np
# Create the 2D array called temps with the given values
# Your code here

Need a hint?

Use np.array() to create a 2D array from a list of lists.

2

Set row and column indexes

Create two variables called row and col. Set row to 1 and col to 2 to select the second row and third column.

NumPy

import numpy as np
temps = np.array([[23, 25, 22], [21, 24, 20], [19, 22, 23]])
# Set row to 1 and col to 2
# Your code here

Need a hint?

Remember that Python uses zero-based indexing, so row 1 is the second row.

3

Access the element at the given row and column

Use the variables row and col to access the element in temps at that position. Store this value in a variable called selected_temp.

NumPy

import numpy as np
temps = np.array([[23, 25, 22], [21, 24, 20], [19, 22, 23]])
row = 1
col = 2
# Access the element at temps[row, col] and store in selected_temp
# Your code here

Need a hint?

Use temps[row, col] to get the element at the specified row and column.

4

Print the selected temperature

Print the value stored in selected_temp.

NumPy

import numpy as np
temps = np.array([[23, 25, 22], [21, 24, 20], [19, 22, 23]])
row = 1
col = 2
selected_temp = temps[row, col]
# Print the selected_temp value
# Your code here

Need a hint?

Use print(selected_temp) to display the value.